Gilbert Johnson Keerthi Distance Algorithm
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High Quality Content by WIKIPEDIA articles! The Gilbert Johnson Keerthi distance algorithm is a method of determining the minimum distance between two convex sets. Unlike many other distance algorithms, it does not require that the geometry data be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplexes to the correct answer using the Minkowski sum (CSO) of two convex shapes. "Enhanced GJK" algorithms use edge information to speed up the algorithm by following edges when looking for the next simplex. This improves performance substantially for polytopes with large numbers of vertices.…mehr

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High Quality Content by WIKIPEDIA articles! The Gilbert Johnson Keerthi distance algorithm is a method of determining the minimum distance between two convex sets. Unlike many other distance algorithms, it does not require that the geometry data be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplexes to the correct answer using the Minkowski sum (CSO) of two convex shapes. "Enhanced GJK" algorithms use edge information to speed up the algorithm by following edges when looking for the next simplex. This improves performance substantially for polytopes with large numbers of vertices.